Information Relationship Visualization System
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Solution Overview
Problem
Existing information processing methods struggle to effectively display and interpret the relationships between observed information and systematically accumulated knowledge, particularly due to the vagueness of fixed quantities and the difficulty in using dictionaries suited for various purposes, leading to challenges in extracting and visualizing relevant information.
Innovation Solution
A system that systematically processes observed information by assigning fixed quantities to relationships between observed information and knowledge accumulations, using techniques like Latent Semantic Analysis and Term Frequency-Inverse Document Frequency (TF-IDF) to display numerical values and graphical representations of these relationships, allowing for a visible and interpretable connection between information objects and knowledge configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed quantities are used to represent relationships between information objects, then information processing becomes systematic, but the results become vague and difficult to interpret
Solution Approach 1:
The patent applies visual metaphors where numerical values are represented through visual attributes such as color intensity, bar length, or graphic size. This transforms abstract numerical relationships into visually interpretable forms, allowing users to perceive information relationships intuitively while maintaining systematic processing through underlying numerical calculations.
2Adaptability or versatility
If dictionaries are used for information interpretation, then language translation and classification become possible, but it becomes difficult to use dictionaries suited for various different purposes
Solution Approach 1:
The patent creates a universal information processing system that can handle multiple types of information relationships (part-whole, composition, classification, etc.) through a single integrated framework. The system uses configurable weight coefficients and visual metaphors that can be adjusted for different information types and purposes, eliminating the need to select different dictionaries for different tasks.
3Measurement precision
If numerical values are assigned to information relationships, then quantitative analysis becomes possible, but the relationships become less visible and harder to understand
Solution Approach 1:
The patent transforms one-dimensional numerical values into multi-dimensional visual representations. Numerical relationships are mapped to visual dimensions such as bar length, color intensity, or graphic size, allowing users to perceive quantitative relationships through visual intuition while the underlying numerical precision is preserved in the calculations.
Data Source
AI summary
A system for visibly processing observed information may include a configuration for systematizing information; a knowledge accumulation housing unit for storing knowledge accumulations from knowledge information belonging to each such configuration; an observed information receiving unit for receiving, from a user, information observed by the user; a fixed quantity processing unit for assigning a fixed quantity to a relationship between the observed information and the knowledge information belonging to each configuration for the knowledge accumulations; and a fixed quantity value display processing unit for displaying a numerical value of the fixed quantity, in accordance with the fixed quantity processing unit, together with its relationship with each configuration of the knowledge accumulations.